Big Data // Big Data Analytics
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1/30/2014
09:06 AM
Doug Henschen
Doug Henschen
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16 Top Big Data Analytics Platforms

Data analysis is a do-or-die requirement for today's businesses. We analyze notable vendor choices, from Hadoop upstarts to traditional database players.
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1010data puts analytics in the cloud 
 
Analytical DBMS: 1010data columnar analytical database. 
In-memory DBMS: None. 
Stream-analysis option: None. 
Hadoop distribution: None.  
Hardware/software systems: Not applicable.
New York-based 1010data launched its analytical, private-cloud service way back in 2000, building a base of customers on Wall Street. Marquis customers include NYSE Euronext and a number of big banks, but the company has also branched out into retail, CPG, gaming, healthcare, government, and telecommunications.
1010data's columnar database supports massively parallel processing for scalability, but it's a proprietary design with its own query language that supports a subset of SQL functions plus broader query types including graph and time-series analyses. It also handles semi-structured data such as social network and machine data. Beyond the database, the company offers a complete stack including data integration, reporting, and data-visualization tools, as well as advanced analytic functions including statistical analysis, optimization, and machine learning.
1010data's private-cloud approach relieves customers of the burden of managing and scaling infrastructure. Centralized management and access controls and APIs support integration with back-end systems as well as broad access to information with 'HIPAA-grade' security. The company has more than 250 customers. In contrast to a cloud provider such as Amazon, which delivers standardized (very-low-cost) services to tens of thousands of customers, 1010data is a custom services provider that crafts private-cloud applications and capabilities matched to customer needs.

1010data puts analytics in the cloud

Analytical DBMS: 1010data columnar analytical database.
In-memory DBMS: None.
Stream-analysis option: None.
Hadoop distribution: None.
Hardware/software systems: Not applicable.

New York-based 1010data launched its analytical, private-cloud service way back in 2000, building a base of customers on Wall Street. Marquis customers include NYSE Euronext and a number of big banks, but the company has also branched out into retail, CPG, gaming, healthcare, government, and telecommunications.

1010data's columnar database supports massively parallel processing for scalability, but it's a proprietary design with its own query language that supports a subset of SQL functions plus broader query types including graph and time-series analyses. It also handles semi-structured data such as social network and machine data. Beyond the database, the company offers a complete stack including data integration, reporting, and data-visualization tools, as well as advanced analytic functions including statistical analysis, optimization, and machine learning.

1010data's private-cloud approach relieves customers of the burden of managing and scaling infrastructure. Centralized management and access controls and APIs support integration with back-end systems as well as broad access to information with "HIPAA-grade" security. The company has more than 250 customers. In contrast to a cloud provider such as Amazon, which delivers standardized (very-low-cost) services to tens of thousands of customers, 1010data is a custom services provider that crafts private-cloud applications and capabilities matched to customer needs.

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D. Henschen
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D. Henschen,
User Rank: Author
1/30/2014 | 11:52:39 AM
It's time for this update
It has been little more than two years since we published our 12 Top Big Data Analytics Players collection, but so much has changed and so many new players have emerged that we needed this update. Over the last 26 months, all the big data-management vendors -- IBM, Microsoft, Oracle, SAP, Teradata -- have really embraced Hadoop. And whether they're adding SQL-on-Hadoop options -- a la Actian, InfiniDB/Calpont, and Pivotal -- or exploiting unprecidented levels of RAM -- as with Kognitio and SAP -- database management system suppliers are changing the scope and speed of their analysis capabilities.

The biggest change, though, is that practitioners are considering the data that they have on hand, the data that they're currenlty throwing away, and the data that they could collect with sensors or smart phones. They're considering all-new applications and, in some cases, entirely new business models. Innovaters may not want to delay or get their hands too dirty with all this technology, however, so we're seeing cloud options from 1010data, Amazon Web Services and others gathering steam.

We may have reached the end of the beginning of the big data era. But it's time to move beyond the speculative hype and get down to the business of on creating breakthrough applications that deliver value. Let 2014 be the year we shift from focusing on what could be to what is actually happening in the world of big data analysis.  
mhummel515
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mhummel515,
User Rank: Apprentice
1/30/2014 | 12:09:03 PM
ParStream - real-time database for big data analytics
Hi Doug,

I very much appreciate your update on the big data analytics vendor market. 

I am curious to find out why you did not include ParStream in your list of big data analytics players. Agreed that the majority of our customers is still in Europe but through our strong presence in Cupertino and Boston we have won numerous customers in the US.

Our focus is on Fast Data - continuous data import at very high bandwidth combined with sub-second response times on billions of data records. 

Through partnerships with leading front-end and ETL tool providers AND Hadoop we offer a super-fast analytics solution that outperforms all product on your list.

I am happy to share with you performance benchmarks and introduce you to our reference customers.

Best
Mike
CEO ParStream
D. Henschen
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D. Henschen,
User Rank: Author
1/30/2014 | 12:53:55 PM
Re: ParStream - real-time database for big data analytics
Thanks for your note. I don't hear much about ParStream, and your list of customers isn't studded with well-know companies. I excluded Exasol for much the same reason -- a number of customers in Germany, but not a presence in North America where we get the vast majority of our readership. Your technology is of interest, however, so feel free to contact me, particularly with customer case example.
Laurianne
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Laurianne,
User Rank: Author
1/30/2014 | 1:03:16 PM
Important Big Data Context
Doug has supplied important context for those people choosing between big data analysis vendors. Please tell us if there are aspects you would like more/less detail on when we do the next roundup. Readers, are you surprised by how much support Hadoop has won from the bigs in the last 24 months?
mhummel515
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mhummel515,
User Rank: Apprentice
1/30/2014 | 1:09:00 PM
Re: ParStream - real-time database for big data analytics
Hi Doug,

I appreciate your interest in ParStream and will make sure to get in contact to provide insights into our product and customer base.

Unfortunately, some of our customers are "shy" and do not want to be named publicly. This unfortunately includes the US customers.

Looking forward to get in touch.



Mike
cbabcock
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cbabcock,
User Rank: Strategist
1/30/2014 | 2:41:29 PM
Revolutionary times, now and then
Doug, you're right, this is a revolutionary time in data management. The last time was when relational database first appeared. I remember sitting through meeting after meeting with then-major vendors, Software AG of North America in Reston, Va.,(Adabas) and John Cullinane, CEO at Cullinane Software (IDMS). They were furious that their partner, IBM, was coming into "their" data management market. "There's no need for IBM to do that." Well, IBM had invented ad hoc data handling and SQL queries. "Their" systems didn't do that. It was a quick lesson in how vendors get flanked. NoSQL systems don't have the same elegance of relational's deisgn, but they're too useful with unstructured data to get swept back under the rug.
HM
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HM,
User Rank: Strategist
1/30/2014 | 3:03:02 PM
Big Data Solution
Doug, one other open source technology to mention at the top of the decision tree one should consider is HPCC Systems from LexisNexis, a data-intensive supercomputing platform for processing and solving big data analytical problems. Their open source Machine Learning Library and Matrix processing algorithms assist data scientists and developers with business intelligence and predictive analytics. Its integration with Hadoop, R and Pentaho extends further capabilities providing a complete solution for data ingestion, processing and delivery. In fact, both libhdfs and webhdfs implementations are available. More at http://hpccsystems.com/h2h 

 
 
EB Quinn
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EB Quinn,
User Rank: Apprentice
1/31/2014 | 8:00:42 AM
Only 16?
There are many more of these "top" solutions, and some of these on the "top" list make no sense whatsoever.  What is the criteria?  Does it have to include Hadoop?  MPP?  Advertiser?  Market share?  Some of the vendors you have included have very little market share, like Pivotal and Microsoft (unless you are incuding Excel).  Where is SAS?  Palantir?  Qlik?  Platfora?  They may not have Hadoop distributions, but they can work with Hadoop just fine (and Platfora is natively based on Hadoop).  Agree with the comment that HPCC should be on this list, way higher than a bunch of the others in terms of proven high end analytics with actual customers.  What is a "platform?"  Cringing.

 

 

 
D. Henschen
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D. Henschen,
User Rank: Author
1/31/2014 | 2:03:48 PM
Read the introduction
This is about platforms for big-data analysis -- as in DBMSs and Hadoop - and I state very clearly in the intro that it does not address analytics companies -- SAS, Qlik, and others you mention -- that focus almost entirely on analytics alone and that tend to work with these platforms. Nor does this address NoSQL or NewSQL databases, which we'll address in a separate collection.
srini s
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srini s,
User Rank: Apprentice
1/31/2014 | 2:36:25 PM
A collection of marketing flyers from 16 vendors
This is a shallow post to introduce a newbie to a biased view of what is available in the market (on Hadoop and it's related technology) if you want to venture into big data. Instead of sitting through a marketing presentation of each of these vendors, or going through their websites, you can see it here. I would have personally preferred the links to the home page of these technologies. It doesn't seem to take an unbiased approach on merits and pitfalls. Why would you choose one over the other.  A comparison on the technologies based on its focus (which of the VVV that it attacks), what is the TCO, quantifying the BIG and qualifying the ANALYTICS in big data analytics. Both Cloudera and Hortonworks are there. We have HP and IBM too and AWS... meh! Could have included some SAN storage providers too :) There seems to be no plane for comparison. There is no connecting element between pages. I would have liked a better organization of thoughts. 

This would have been a ground breaking post in 2006. But now.. pass!

-Srini

 
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